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  • View in gallery

    Winter climatological zonal wind speed (m s−1) at 300 hPa.

  • View in gallery

    Composite maps of the zonal wind anomaly (m s−1) at 300 hPa for (a) strong monsoon years and (b) weak monsoon years. The hatchings indicate the areas exceeding the 90% significance level.

  • View in gallery

    Three-dimensional wave activity fluxes, W, associated with the high-frequency disturbances for (a) strong monsoon years, (b) weak monsoon years, and (c) their difference (strong minus weak). The vectors indicate the horizontal components of W and the shading indicates the vertical component of W at 300 hPa with units of m2 s−2. The hatchings in (c) indicate the areas exceeding the 90% significance level.

  • View in gallery

    ∇ ⋅ W anomalies associated with the high-frequency disturbances for (a) strong and (b) weak monsoon years at 300 hPa in units of 10−6 m s−2. The hatchings indicate the areas exceeding the 90% significance level.

  • View in gallery

    As in Fig. 3, but for the low-frequency disturbances.

  • View in gallery

    As in Fig. 4, but for the low-frequency disturbances.

  • View in gallery

    The diabatic heating anomaly for (a) strong and (b) weak monsoon winters at 500 hPa with units of 10−5 K s−1. The hatchings indicate the areas exceeding the 90% significance level.

  • View in gallery

    The steady-state response of the zonal wind (m s−1) at 300 hPa to the total forcings for (a) strong and (b) weak monsoon winters.

  • View in gallery

    The steady-state response of the zonal wind (m s−1) at 300 hPa to the forcing separated by (a),(b) diabatic heating, (c),(d) nonlinear effects due to the high-frequency disturbances, and (e),(f) nonlinear effects due to the low-frequency disturbances for (left) strong and (right) weak monsoon winters.

  • View in gallery

    The response of 300 hPa zonal wind (m s−1) over 25°–45°N, 80°E–180° to the total forcings (All), diabatic heating (Q′), nonlinear effects due to the high-frequency disturbances (Nh′), and nonlinear effects due to the low-frequency disturbances (Nl′) for the (left) strong and (right) weak monsoon years. Gray, red, orange, and blue bars show the response to the forcings over the entire globe (90°S–90°N), low latitudes (20°S–20°N), midlatitudes (20°–50°N), and high latitudes (50°–80°N), respectively.

  • View in gallery

    Composite maps of the zonal wind anomaly (m s−1) at 300 hPa for (a) the 7 AO+ years and (b) the 7 AO− years. Also shown are the steady-state response of 300-hPa zonal wind (m s−1) to (c),(d) the total forcings, (e),(f) diabatic heating, and (g),(h) nonlinear effects for (left) the 7 AO+ years and (right) the 7 AO− years.

  • View in gallery

    As in Fig. 11, but for SOI.

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Roles of Intraseasonal Disturbances and Diabatic Heating in the East Asian Jet Stream Variabilities Associated with the East Asian Winter Monsoon

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  • 1 National Institute for Environmental Studies, Tsukuba, Japan
  • | 2 Atmosphere and Ocean Research Institute, Chiba, Japan
  • | 3 Japan Agency for Marine-Earth Science and Technology, Yokosuka, Japan
  • | 4 National Institute for Environmental Studies, Tsukuba, and Atmosphere and Ocean Research Institute, Chiba, Japan
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Abstract

This study evaluates the relative importance of diabatic heating and intraseasonal disturbances with regard to the variabilities of the East Asian jet stream (EAJS) associated with the East Asian winter monsoon (EAWM). First, strong and weak monsoon years are selected based on the EAWM index of Jhun and Lee, which is highly correlated with the monsoon northerlies between the Eurasian continent and the Pacific. The EAJS is stronger and narrower in strong monsoon years and weaker and wider in weak monsoon years. Model experiments were performed to investigate the atmospheric response to the diabatic heating and the eddy–mean flow feedback from the intraseasonal disturbances. The diabatic heating is closely related to the convective activities. The intraseasonal disturbances include high-frequency components with periods of 3–10 days and low-frequency components with periods of 10–90 days. The model results indicate that the diabatic heating plays a major role maintaining the stronger and weaker EAJS in the strong and weak monsoon years, respectively, whereas the impacts of the eddy feedback are relatively small.

Denotes content that is immediately available upon publication as open access.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Nagio Hirota, nagioh@gmail.com

Abstract

This study evaluates the relative importance of diabatic heating and intraseasonal disturbances with regard to the variabilities of the East Asian jet stream (EAJS) associated with the East Asian winter monsoon (EAWM). First, strong and weak monsoon years are selected based on the EAWM index of Jhun and Lee, which is highly correlated with the monsoon northerlies between the Eurasian continent and the Pacific. The EAJS is stronger and narrower in strong monsoon years and weaker and wider in weak monsoon years. Model experiments were performed to investigate the atmospheric response to the diabatic heating and the eddy–mean flow feedback from the intraseasonal disturbances. The diabatic heating is closely related to the convective activities. The intraseasonal disturbances include high-frequency components with periods of 3–10 days and low-frequency components with periods of 10–90 days. The model results indicate that the diabatic heating plays a major role maintaining the stronger and weaker EAJS in the strong and weak monsoon years, respectively, whereas the impacts of the eddy feedback are relatively small.

Denotes content that is immediately available upon publication as open access.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Nagio Hirota, nagioh@gmail.com

1. Introduction

The East Asian winter monsoon (EAWM) refers to large-scale atmospheric circulations primarily driven by differential heating between the land and sea (e.g., Zhang et al. 1997). The Siberian high and the Aleutian low are located over the colder Eurasian continent and the warmer Pacific Ocean, respectively. The zonal pressure gradients between these pressure systems balance via geostrophic northwesterlies from Siberia to East Asia around 30°N. In addition, a low-pressure center is located around the Maritime Continent, which is associated with the surface northeasterlies to the south of 30°N (Wang and Chen 2014). The variabilities in the monsoon northerlies and the associated cold surges exert large social and economic impacts on East Asian countries (e.g., Wang et al. 2009).

The cold air advection of the monsoon northerlies enhances meridional temperature gradients around Japan, causing the East Asian jet stream (EAJS) to be stronger and narrower there (Jhun and Lee 2004). The jet’s strength and structure influence synoptic wave activities in the storm track. In general, synoptic wave activities increase with the wind speed and the baroclinicity of the jet. However, when the jet speeds are greater than 45 m s−1, as they are over East Asia, the synoptic wave activities are observed to be negatively correlated with the wind speeds. Nakamura (1992) and Nakamura and Sampe (2002) explained that this reduction in storm activity with a stronger EAJS occurs because synoptic eddies move more quickly out of the storm track region, allowing them less time to amplify. In addition to the jet strength, Harnik and Chang (2004) suggested that the narrowness of the EAJS is also an important factor reducing synoptic wave activity. Meanwhile, the synoptic activity influences the EAJS via the momentum transport by the associated eddy flux (Wettstein and Wallace 2010; Athanasiadis et al. 2010; Li and Wettstein 2012).

Previous studies have also discussed the relationship between the EAWM and quasi-stationary planetary waves (with a period of over ~10 days), which vary more slowly than synoptic waves. Wang et al. (2009) examined interdecadal variations of the EAWM during the period 1957–2002. Both the Siberian high and the Aleutian low were significantly weakened around 1988, possibly due to decreased snow cover over the Eurasian continent. The weakening of pressure systems corresponds to the weakening of planetary waves. They also showed that the anomalous planetary waves propagate southward, resulting in the convergence of wave activities at midlatitudes and divergence at higher latitudes. The eddy feedback from the divergent and convergent wave activities generally accelerates and decelerates the westerlies, respectively (Hoskins et al. 1983; Plumb 1986; Takaya and Nakamura 2001). Therefore, Wang et al. (2009) explained that the anomalous planetary waves associated with the weakening EAWM decelerate the EAJS and accelerate the polar jet. The weaker EAJS and the stronger polar jet are typical features of a weak EAWM (Jhun and Lee 2004). The variabilities of the Siberian high and the EAWM are also related with the Arctic Oscillation (AO), which is the dominant annular mode of the atmospheric variabilities in the Northern Hemisphere (Gong et al. 2001).

Furthermore, diabatic heating associated with convective activities may play a role in EAWM variabilities. Valdes and Hoskins (1989) investigated atmospheric responses to observed diabatic heating using a multilevel primitive equation model linearized about the observed zonal mean flow. Their results suggested that the maintenance of the subtropical jet is associated primarily with diabatic forcings. Even though they emphasized the importance of diabatic heating at midlatitudes, diabatic heating in the tropics may also be important for EAWM variabilities. Zhang et al. (1997) showed that strong cold-surge events are found more frequently in La Niña years than in El Niño years. They speculated that convective activities over maritime continents are responsible for EAWM variabilities associated with El Niño–Southern Oscillation (ENSO). Meanwhile, Li and Wettstein (2012) showed that tropical diabatic heating is positively correlated with the strength of the EAJS.

This study aims to advance our understanding of to what extent the EAJS variabilities are associated with the forcings of the diabatic heating and the eddy feedback from the intraseasonal disturbances. As for the intraseasonal disturbances, we consider the high-frequency components (e.g., the synoptic waves) and the low-frequency components (e.g., a blocking high or quasi-stationary planetary waves) separately.

As described above, previous studies illustrated how these forcings are different under the strong and weak EAJS conditions. However, it is still not clear to what extent the forcings by diabatic heating and intraseasonal disturbances are maintaining the EAJS. This is a challenging issue because the observational data include results of the forcings as well as the EAJS influence on the forcings. As will be described in section 4, a linear model used in this study isolates the impacts of the forcings on the EAJS variabilities. Note that investigating impacts of diabatic heating and eddy forcing by using a linear model is discussed in many previous studies (Hoskins and Karoly 1981; Branstator 1990; Valdes and Hoskins 1989; Held et al. 1989; Hoskins and Valdes 1990; Watanabe and Kimoto 2000; Watanabe and Jin 2003; Hirota et al. 2005; Mori and Watanabe 2008; Hirota and Takahashi 2012). We expect our results will help us better understand the EAWM, simulations of which are difficult even in the current state-of-the-art climate models (Wei et al. 2014; Gong et al. 2014, 2015).

The data used in this study are described in section 2, the analysis results are provided in section 3, the model experiments are described in section 4, and the summary and discussion are given in section 5.

2. Data

The data used in this study are 6-hourly and monthly data from the Japanese 55-Year Reanalysis (JRA-55; Kobayashi et al. 2015) for 58 winters from December 1958 to February 2016. Our winter comprises three months: December, January, and February (e.g., for the 1958/59 winter, the average is for December 1958–February 1959). The datasets were provided by the Japan Meteorological Agency (JMA). The climatological mean was calculated as an average from the 1958/59 to 2015/16 winters, and the anomalies were the deviations from the climatological mean.

3. Data analyses

a. EAWM variations

The climatological mean fields for the winters of 1958/59–2015/16 are characterized by the Siberian high and the Aleutian low in the sea level pressure field and the predominant northerly winds over northeastern Asia in the lower troposphere. The EAJS flow in the upper troposphere at 300 hPa is illustrated in Fig. 1. The maximum wind speed is approximately 65 m s−1 and the core is evident just south of Japan. The position of the jet core is closely related to the enhanced meridional temperature gradient in the lower troposphere via the thermal wind relationship. As the northerly winter monsoon flow over northeastern Asia strengthens, it brings in additional cold air and produces a stronger meridional temperature gradient. Therefore, a stronger monsoon flow leads to a stronger EAJS over the East Asian region (e.g., Jhun and Lee 2004; Lee et al. 2010).

Fig. 1.
Fig. 1.

Winter climatological zonal wind speed (m s−1) at 300 hPa.

Citation: Journal of Climate 31, 7; 10.1175/JCLI-D-16-0390.1

To measure the strength of the EAWM, the East Asian winter monsoon index (EAWMI) formulated by Jhun and Lee (2004) was adopted. The EAWMI is defined as the difference in the 300-hPa zonal wind anomaly from the climatological mean between the two regions, 27.5°–37.5°N, 110°–170°E and 50°–60°N, 80°–140°E. This index is closely related to the monsoon northerlies and has a large negative correction of −0.8 with the surface temperature around the Korean Peninsula and Japan (Jhun and Lee 2004). In general, it is difficult to measure the entire EAWM using a single index. However, for this study, the EAWMI is suitable because our intention is to investigate the localized baroclinicity associated with the EAJS over northeast Asia. We removed the linear trend from the EAWMI time series because we are focusing on the interannual variabilities. We selected the 10 strongest monsoon years (EAWMI larger than 0.79 standard deviations) and the 10 weakest monsoon years (EAWMI smaller than −0.90 standard deviations) from the period of 1958/59 to 2015/16. The 10 strong winter monsoon years were 1961/62, 1967/68, 1969/70, 1976/77, 1980/81, 1983/84, 1984/85, 1985/86, 2005/06, and 2011/12 and the 10 weak winter monsoon years were 1958/59, 1968/69, 1971/72, 1972/73, 1978/79, 1989/90, 1991/92, 1997/98, 2006/07, and 2013/14. Moreover, we have confirmed that similar results are obtained even when using other indices for the winter monsoon, as will be discussed in section 5. A bootstrap method was used to test the statistical significance as follows. We randomly selected 10 years from the analyzed 58 winters and calculated an anomaly of the 10-yr average. We repeated this calculation for 1000 times and generated a distribution of the 10-yr-average anomalies. The anomalies of the strong and weak monsoon years are considered significant at level of 90% if they are in the top or bottom 5% of the distribution [see also Fox (2008) and Yamashita et al. (2015)].

The composite maps of the zonal wind anomalies at 300 hPa for the strong and weak monsoon years are shown in Fig. 2. Most of the anomalies over East Asia were significant at a 90% level (hatchings in Fig. 2). The anomaly patterns of the meteorological variables in the strong monsoon years are in clear contrast to those in the weak monsoon years. In strong monsoon years, the westerly wind anomaly around Japan corresponds to the strengthening of the EAJS, and the easterly wind anomaly to its north and south indicates that the latitudinal width of the EAJS is narrow compared with the climatological mean (Fig. 2a). In weak monsoon years, the EAJS becomes weak and an easterly wind anomaly appears around Japan (Fig. 2b). The latitudinal width of the EAJS is wider in weak monsoon years than in strong monsoon years. A high (low) pressure anomaly appears around the Siberian high and a low (high) pressure anomaly around the Aleutian low during the strong (weak) monsoon years (cf. Fig. 6 in Jhun and Lee 2004). At 850 hPa, a cooler (warmer) temperature anomaly spreads from the northeast of China to Japan, and a warmer (cooler) temperature anomaly covers the surrounding areas during the strong (weak) monsoon years.

Fig. 2.
Fig. 2.

Composite maps of the zonal wind anomaly (m s−1) at 300 hPa for (a) strong monsoon years and (b) weak monsoon years. The hatchings indicate the areas exceeding the 90% significance level.

Citation: Journal of Climate 31, 7; 10.1175/JCLI-D-16-0390.1

b. Intraseasonal disturbances and diabatic heating

To examine the intraseasonal disturbances, we first filtered the 6-hourly data in the time domain using the Hamming filter (Hino 1977; Hamming 1998). We defined the waves with periods of 3–10 days as high-frequency intraseasonal components, whereas the waves with periods of 10–90 days were defined as low-frequency intraseasonal components. Our spectral analysis indicated that they were the dominant periods of the waves associated with the EAWM variabilities (not shown).

The interactions between the intraseasonal waves and the seasonal (winter) mean fields were investigated using the wave activity flux W formulated by Takaya and Nakamura (2001). The divergence (convergence) of the wave activity flux indicates a source (sink) region for wave activity and is proportional to the tendency of the pseudo wave energy. Its expression in the pressure coordinate system is given as
eq1
eq2
where ψ is the streamfunction, f is the Coriolis parameter, S is the atmospheric stability parameter, Cu is the prescribed phase velocity, M is the pseudomomentum, and other notations are standard. Overbars and primes denote the basic-state quantities and the anomalies, respectively. The subscripts x, y, and p indicate the derivatives. The phase velocity (Cu) is estimated based on one-point correlation maps of streamfunction in the upper troposphere as in Takaya and Nakamura (2001).

Figure 3 shows the horizontal and vertical fluxes of the 3–10-day time-filtered W at 300 hPa for strong and weak monsoon years and the difference between them. Eastward and vertical upward fluxes are seen over eastern Japan in both strong and weak monsoon years. These areas correspond to the North Pacific storm track region. Comparing the strong and weak years (Fig. 3c), vertical upward fluxes are much weaker over the Pacific during the strong monsoon years. The weakened wave activities in the strong monsoon years are consistent with the findings of Nakamura (1992), Nakamura et al. (2002), and Harnik and Chang (2004).

Fig. 3.
Fig. 3.

Three-dimensional wave activity fluxes, W, associated with the high-frequency disturbances for (a) strong monsoon years, (b) weak monsoon years, and (c) their difference (strong minus weak). The vectors indicate the horizontal components of W and the shading indicates the vertical component of W at 300 hPa with units of m2 s−2. The hatchings in (c) indicate the areas exceeding the 90% significance level.

Citation: Journal of Climate 31, 7; 10.1175/JCLI-D-16-0390.1

The divergence of W (i.e., ∇ ⋅ W) is applied as a measure of the effects of the high-frequency disturbances on the seasonal mean fields. The dominant term of W in the nearly zonal basic state is the zonal momentum flux with the negative sign , and its divergence (convergence) suggests the westerly accelerations (decelerations). The ∇ ⋅ W in Fig. 4 shows only few statistically significant anomalies, suggesting that their feedback effects are limited. In strong monsoon years, a convergence anomaly of ∇ ⋅ W appears around northern Japan, which suggests relaxing of the westerly wind anomaly of the EAJS (Fig. 2a). Quantitative impacts of the intraseasonal disturbances on the EAJS will further be examined using the model in the next section.

Fig. 4.
Fig. 4.

∇ ⋅ W anomalies associated with the high-frequency disturbances for (a) strong and (b) weak monsoon years at 300 hPa in units of 10−6 m s−2. The hatchings indicate the areas exceeding the 90% significance level.

Citation: Journal of Climate 31, 7; 10.1175/JCLI-D-16-0390.1

Figure 5 displays the horizontal and vertical fluxes of W associated with the low-frequency disturbances at 300 hPa for strong monsoon years, weak monsoon years, and the difference between them. Eastward fluxes are seen in both the strong and weak monsoon years over the North Pacific. Comparing the difference in the fluxes between the strong and weak monsoon years (Fig. 5c), the eastward propagation is slightly weaker around Japan in strong monsoon years. The downward anomaly in the midlatitudes over the Pacific is significant.

Fig. 5.
Fig. 5.

As in Fig. 3, but for the low-frequency disturbances.

Citation: Journal of Climate 31, 7; 10.1175/JCLI-D-16-0390.1

Figure 6 illustrates the anomalous ∇ ⋅ W associated with the low-frequency components in strong and weak monsoon years. A weak positive anomaly of ∇ ⋅ W appears around the East China Sea (25°N, 135°E) in the strong monsoon years (Fig. 6a), and a weak negative anomaly appears around Japan in the weak monsoon years (Fig. 6b). The areas of the divergence (convergence) anomaly of ∇ ⋅ W for strong (weak) years are consistent with the westerly (easterly) anomaly near Japan shown in Fig. 2, although the significance of these anomalous ∇ ⋅ W is small.

Fig. 6.
Fig. 6.

As in Fig. 4, but for the low-frequency disturbances.

Citation: Journal of Climate 31, 7; 10.1175/JCLI-D-16-0390.1

The distribution of diabatic heating anomalies in strong and weak monsoon years is shown in Fig. 7. The diabatic heating was estimated as a residual of the thermodynamic equation using the 6-hourly reanalysis data (Yanai et al. 1973). In strong monsoon years (Fig. 7a), diabatic cooling is observed in the equatorial Pacific Ocean (10°S–10°N, 160°E–120°W) and diabatic heating occurs to the west of that region (15°S–15°N, 100°–150°E). Moreover, significant anomalies are also located over the East China Sea and Japan, which will be shown to be important for the EAJS variabilities in the next section. The diabatic heating in weak monsoon years shows an approximately opposite pattern (Fig. 7b). The horizontal distributions of the diabatic heating are very similar to those of the precipitation and SST anomalies (not shown). Therefore, the diabatic heating is likely to be related to anomalous convective activities (e.g., Hirota and Takahashi 2012). The impacts of the diabatic heating on the EAJS will be described in the next section.

Fig. 7.
Fig. 7.

The diabatic heating anomaly for (a) strong and (b) weak monsoon winters at 500 hPa with units of 10−5 K s−1. The hatchings indicate the areas exceeding the 90% significance level.

Citation: Journal of Climate 31, 7; 10.1175/JCLI-D-16-0390.1

4. Experiments using a linear model

a. Model

Numerical experiments were performed to examine the relative importance of the diabatic heating and the eddy feedback from the intraseasonal disturbances. The model used in this study is a linear primitive model developed by Hirota and Takahashi (2012). The governing equations of the model are the primitive equations linearized about the climatological basic state in sigma coordinate system. The equations of anomalous variables linearized about a basic state are written as
e1
where X is a vector of prognostic variables (vorticity, divergence, and temperature), is the linear dynamical operator, and F is a forcing vector. The exact form of the equations on the model is given in the appendix.

The horizontal resolution of the model is T42 (~2.8°) and the model has 58 vertical levels. Rayleigh friction, Newtonian cooling, and horizontal diffusion were included. The e-folding time of the friction and cooling was set to 1 day for 1.0 < σ < 0.95, 3 days for 0.95 < σ < 0.9, 5 days for 0.9 < σ < 0.85, 30 days for 0.85 < σ < 0.035, and 1 day for 0.035 < σ < 0.0083 (Branstator 1990; Watanabe and Jin 2003). The strong friction at the boundary layers mimics a turbulent mixing process. The e-folding time of horizontal diffusion was set to 0.5 day for the largest wavenumber.

The linear primitive model calculates a linear response (X′) to forcings (F′) of the diabatic heating and the eddy feedback terms associated with the intraseasonal disturbances. This model does not include the nonlinear processes and the moist processes. Instead, we prescribed (not neglected) the corresponding external forcings diagnosed from the reanalysis data. We are only examining the impact of the heating and the eddy forcing on EAJS rather than the full interactive process of the forcings and the jet. The diabatic heating is primarily due to the condensation heating of the precipitation anomalies caused by convective activities. The nonlinear terms arise primarily from the convergence of the horizontal vorticity flux associated with the high- and low-frequency disturbances. Generally, they correspond to ∇ ⋅ W (Hirota and Takahashi 2012). This method of calculating the response to the prescribed forcings is advantageous in isolating the impacts of the forcings on the EAJS variabilities, but is also a limitation as the influence of the EAJS on the forcings is not simulated. This limitation should be kept in mind especially when discussing regional importance of the forcings. This issue will be discussed in section 5.

The linear model was integrated for 30 days with the prescribed forcings imposed at each time step. The model response reached a near-steady state on the 20th day (not shown). Therefore, the responses to the forcings discussed are an average from days 20 to 30. The linear model’s purpose here is to get a steady state solution before baroclinic instability sets in, thus the short integration time. The fast response of the atmosphere is confirmed in previous studies (Rodwell and Hoskins 1996; Enomoto et al. 2003; Watanabe and Jin 2003). Assuming the steady state, the response can be written as
eq3

In this linear model, the climatological basic state, which determines the linear dynamical operator , was prescribed using the reanalysis data. This is another advantage of the linear model over the general circulation models (GCMs) where the realistic simulation of the climatology is needed even when our interest is only on the anomalies from the climatological basic state. Although the climatology was prescribed in the linear model, we still need to validate simulated anomalies as described in the next subsection.

b. Results

To validate the linear model, we calculated the steady-state responses of the zonal wind to the total external forcings of the diabatic heating with the high- and low-frequency nonlinear terms over the entire globe at all vertical levels. The responses shown in Fig. 8 reproduce the observed anomaly pattern shown in Fig. 2. The easterly–westerly–easterly (westerly–easterly–westerly) responses correspond to the stronger (weaker) and narrower (wider) EAJS in the strong (weak) monsoon years. Moreover, the northerly and the cold air advection that are described as being important for the EAJS variabilities (see section 1) are also reproduced in the model (not shown). The similarities between the results from our model and the reanalysis data validate that this model can realistically simulate the linear dynamics of the anomalies associated with prescribed forcings on the climatological basic states.

Fig. 8.
Fig. 8.

The steady-state response of the zonal wind (m s−1) at 300 hPa to the total forcings for (a) strong and (b) weak monsoon winters.

Citation: Journal of Climate 31, 7; 10.1175/JCLI-D-16-0390.1

Next, the responses to the diabatic heating and to the nonlinear eddy forcings were calculated separately, as illustrated in Fig. 9, for the strong and weak monsoon years. From Figs. 8a,b and 9a,b, we see that, even if the forcing is only provided by the diabatic heating (without the eddy feedback effects), the westerly and easterly anomalies of the EAJS are reproduced in the strong and weak monsoon years, respectively. Therefore, we conclude that diabatic heating plays a primary role in maintaining the anomaly pattern associated with EAWM variabilities.

Fig. 9.
Fig. 9.

The steady-state response of the zonal wind (m s−1) at 300 hPa to the forcing separated by (a),(b) diabatic heating, (c),(d) nonlinear effects due to the high-frequency disturbances, and (e),(f) nonlinear effects due to the low-frequency disturbances for (left) strong and (right) weak monsoon winters.

Citation: Journal of Climate 31, 7; 10.1175/JCLI-D-16-0390.1

Figures 9c and 9d show the zonal wind anomaly patterns as responses to the nonlinear eddy effects due to the high-frequency components in the strong and weak monsoon years, respectively. In the strong monsoon years, the weak easterly response (Fig. 9c) over Japan is consistent with the eddy feedback from the high-frequency components (Fig. 4a), which is counteracting the westerly anomaly of the EAJS (Fig. 2a), whereas in the weak monsoon years the response to the high-frequency components has almost no contribution (Fig. 9d). Figures 9e and 9f show the zonal wind anomaly patterns of the response to eddy effects due to the low-frequency component in the strong and weak monsoon years, respectively. The results show that the low-frequency components partially contribute to the acceleration and deceleration of the EAJS near Japan in the strong and weak monsoon years, respectively. However, given that the anomalous ∇ ⋅ W shown in Fig. 6 has very noisy horizontal structure with weak statistical significance, the contributions of the low-frequency components might not be robust.

We further performed experiments calculating the linear responses to forcings over 0°–360°E confined to low latitudes (20°S–20°N), midlatitudes (20°–50°N), and high latitudes (50°–80°N) separately. Contributions from each forcing to the zonal wind response averaged over the EAJS (25°–40°N, 90°E–160°W) were summarized in Fig. 10. In the strong monsoon years, the diabatic heating in the midlatitudes is the major factor maintaining the response of EAJS. The eddy feedback from the low-frequency disturbances in the low and high latitudes also plays some roles in the jet acceleration. Similarly, in the weak monsoon years, the diabatic heating in the midlatitudes shows the dominant contributions to the deceleration of the EAJS with smaller effects from the low-frequency disturbances in the low and high latitudes.

Fig. 10.
Fig. 10.

The response of 300 hPa zonal wind (m s−1) over 25°–45°N, 80°E–180° to the total forcings (All), diabatic heating (Q′), nonlinear effects due to the high-frequency disturbances (Nh′), and nonlinear effects due to the low-frequency disturbances (Nl′) for the (left) strong and (right) weak monsoon years. Gray, red, orange, and blue bars show the response to the forcings over the entire globe (90°S–90°N), low latitudes (20°S–20°N), midlatitudes (20°–50°N), and high latitudes (50°–80°N), respectively.

Citation: Journal of Climate 31, 7; 10.1175/JCLI-D-16-0390.1

5. Discussion and summary

This study focused on understanding the relative importance of diabatic heating and eddy–mean flow feedback effects due to intraseasonal disturbances in the EAJS variabilities associated with the EAWM. As for the intraseasonal disturbances, we considered high-frequency components with periods of 3–10 days (e.g., synoptic waves) and low-frequency components with periods of 10–90 days (e.g., a blocking high or quasi-stationary planetary waves) separately based on the spectral analysis. The EAWM index of Jhun and Lee (2004) was used to select the strong monsoon years and the weak monsoon years.

The composite analysis of the JRA-55 reanalysis data indicates that in the strong monsoon years, the northerlies between the Eurasian continent and the Pacific are stronger and the EAJS is stronger and narrower, as in previous studies. The diabatic heating anomalies associated with the stronger monsoon are negative over the East China Sea and Japan. These heating anomalies are related to convective activities. The intraseasonal disturbances are less active over the Pacific. The anomalies of wave activity flux for the low-frequency components are divergent over the East China Sea. These anomalies of the large-scale circulations, the intraseasonal wave activities, and the diabatic heating are essentially opposite signs in weak monsoon years.

We performed linear model experiments to examine the roles of the diabatic heating and the intraseasonal disturbances in the EAJS variabilities. The model results indicated that the diabatic heating play a major role in the maintaining the westerly anomaly of the EAJS in the strong monsoon years and the eastern anomaly in the weak monsoon years. The feedback from the low-frequency components also contributes to the EAJS variabilities near Japan, whereas the feedback from the high-frequency components shows almost no contributions. As the statistical significance of the anomalous ∇ ⋅ W is weak, the impacts of the eddy forcing need further exploration in future study.

This study used the EAWMI of Jhun and Lee (2004), which is highly correlated with the EAWM circulations and the surface temperature over East Asia. To support the robustness of our results, we have done the same analyses using two similar indices: the sea level pressure difference between East Siberia (50°–70°N, 100°–120°E) and the western North Pacific (30°–50°N, 150°–170°E), which is more directly related to the monsoon northerlies, and 200-hPa zonal wind averaged over 30°–35°N, 130°–160°E, which is a more direct measure of the EAJS strength as defined by Yang et al. (2002). The correlation coefficients of EAWMI with these indices of the pressure difference and the EAJS strength are 0.84 and 0.86, respectively. The EAJS is stronger (weaker) when these indices are larger (smaller), consistent with the previous studies. The results of the model experiments based on the composites using these alternative indices are very similar to those using the EAWMI. In particular, the EAJS variabilities are mainly related with the diabatic heating (not shown).

Next, we discuss relationships of EAWMI with the AO and ENSO because they are considered important factors for the EAWM variabilities (Zhang et al. 1997; Gong et al. 2001; Yang et al. 2002). An AO index (AOI) used here is defined as the principal components of the leading empirical orthogonal function mode of 1000-hPa geopotential height poleward of 20°N (http://www.cpc.ncep.noaa.gov/products/precip/CWlink/daily_ao_index/history/method.shtml). As we have done using EAWMI, we examined composites of years with the 10 largest AOI (AO+) and the 10 smallest AOI (AO−). The composite maps of zonal wind anomalies in Figs. 11a,b show that the EAJS is weaker in the AO+ years and stronger in the AO− years. The model responses to diabatic heating (Figs. 11e,f) indicate that these zonal wind anomalies are mainly related to the diabatic heating. Note that the model-simulated responses to all forcings associated with AO (Figs. 11c, d) show some disagreements with the composite anomalies (Figs. 11a,b). For example, the EAJS deceleration in the AO+ years is not reproduced over the Pacific. Further exploration of the AO impacts on the EAJS is beyond the scope of this paper.

Fig. 11.
Fig. 11.

Composite maps of the zonal wind anomaly (m s−1) at 300 hPa for (a) the 7 AO+ years and (b) the 7 AO− years. Also shown are the steady-state response of 300-hPa zonal wind (m s−1) to (c),(d) the total forcings, (e),(f) diabatic heating, and (g),(h) nonlinear effects for (left) the 7 AO+ years and (right) the 7 AO− years.

Citation: Journal of Climate 31, 7; 10.1175/JCLI-D-16-0390.1

As for ENSO, we used the Southern Oscillation index (SOI; http://www.cpc.noaa.gov/products/analysis_monitoring/ensocycle/soi.shtml) defined as pressure differences between Tahiti and Darwin. The composite maps of years with the 10 largest SOI (SOI+) and the 10 smallest SOI (SOI−) are shown in Figs. 12a,b. In the SOI+ (SOI−) years, the EAJS is significantly weakened (strengthened) over the central Pacific, and smaller anomalies with the opposite signs are found over East Asia (25°–40°N, 80°–150°E). The diabatic heating seems to be responsible for the anomalies over East Asia (Figs. 12e,f).

Fig. 12.
Fig. 12.

As in Fig. 11, but for SOI.

Citation: Journal of Climate 31, 7; 10.1175/JCLI-D-16-0390.1

The correlation coefficients of EAWMI with AOI and SOI are −0.2 (explaining 4% of the variance) and 0.24 (6%), respectively. These factors explain only a small part of the EAWM variabilities, indicating that other factors (e.g., SSTs in the extratropics, snow cover over the Eurasian continent, and so on) are also important. Note that the correlation between AOI and SOI is not significant, suggesting that AO and ENSO are affecting EAWM independently.

As previously mentioned, in the model used in this study, the diabatic heating and the eddy forcing are prescribed, and both are not influenced by simulated linear dynamics. This helped to isolate the impacts of the forcings on the EAJS variability. However, in the real atmosphere, the accelerated (or decelerated) zonal wind of the EAJS influences storm activities, thus the diabatic heating and the nonlinear terms. The midlatitude diabatic heating having the largest contribution to the EAJS variabilities (Fig. 10) partly results from precipitation associated with the modulated EAJS forced from the low or high latitudes. Such indirect interactions are not simulated in the linear model. Instead, the results of those interactions diagnosed using the reanalysis data are prescribed (not neglected) in the linear model. To investigate these two-way interactions, GCMs with the nonlinear dynamics and the moist processes should be used in future work.

Acknowledgments

The authors appreciate three anonymous reviewers for their helpful comments and suggestions to improve the manuscript. This study was supported by the Integrated Research Program for Advancing Climate Models and KAKENHI (JP15H02132, JP16K16186) of the Ministry of Education, Culture, Sports, Science, and Technology, Japan, and by the Environment Research and Technology Development Fund (2-1503) of Environmental Restoration and Conservation Agency, Japan. The Grid Analysis and Display System was used to plot the figures.

APPENDIX

Model

The governing equations of the model used in this study are the primitive equations linearized about the climatological basic state in sigma coordinate system [longitude λ, latitude ϕ, and sigma σ (= pressure/surface pressure)]. The primitive equations of anomalous variables linearized about a basic state are
eq4
eq5
eq6
where ξ is vorticity, D is divergence, T is temperature, , u is horizontal wind, is vertical velocity, Tp is temperature deviation from reference temperature (= 300 K), Tυ is virtual temperature, , , Q is heating rate, are nonlinear forcings, R is the radius of Earth, Ω is the angular speed of Earth’s rotation, Rd is gas constant of dry air, Cp is the specific heat of dry air, and κ = Rd/Cp. The linear damping and ∇h2 horizontal diffusion were included with the time scale of τ and the coefficients of ν, respectively. This model calculates a linear response for the prescribed forcings of Q′ and .

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